Biology subjects

Blazej, P.

Publications and source records attributed to Blazej, P..

4 recordsLinked to original sources

bioRxiv2025

Diverse tendencies in codon usage evolution of SARS-CoV-2 genes

The dynamic evolution of SARS-CoV-2 virus since the COVID-19 outbreak in late 2019 has raised questions about potential evolutionary trends in protein-coding sequences and their adaptation to the human host. To address this, we compiled a dataset of 94,571 complete genomes with known collection dates, spanning from January 2020 to October 2024. Using a novel representation of codon usage, we recoded SARS-CoV-2 protein-coding sequences to strings of labels reflecting the human synonymous codon usage. Our analysis reveals different evolutionary pathways in the codon usage between structural, non-structural and accessory protein-coding sequences from the coronavirus. The genes coding for structural proteins tend to exhibit a less optimal adaptation to the human codon usage, whereas open reading frames ORF1a and ORF1ab encoding non-structural proteins show an opposite trend. The sequences for the accessory proteins demonstrated a variable tendency to change the codon preferences. The evolution of the more optimal codon usage in ORF1a and ORF1ab sequences can be associated with a higher speed and efficiency of translation of the coded polyproteins. Following their cleavage, the products play important roles in viral replication and transcription. Thus, the adaptation of their codons can increase the virus proliferation. In contrast, alterations in codon usage within structural protein-coding sequences may be associated with changes in their less accurate translation and folding during the synthesis, which can provide an advantage in evading the host immune response. The results show that codon usage adaptations to the human host differ based on the gene type and function, reflecting a balance between their conflicting evolutionary pressures. Our findings on variations in codon usage among coronavirus genes provide valuable insights that can aid in developing new strategies for the optimization of codons in vaccine mRNA and DNA for emerging strains.

bioinformatics↗

bioRxiv2020

Some theoretical aspects of reprogramming the standard genetic code

1Reprogramming of the standard genetic code in order to include non-canonical amino acids (ncAAs) opens a new perspective in medicine, industry and biotechnology. There are several methods of engineering the code, which allow us for storing new genetic information in DNA sequences and transmitting it into the protein world. Here, we investigate the problem of optimal genetic code extension from theoretical perspective. We assume that the new coding system should encode both canonical and new ncAAs using 64 classical codons. What is more, the extended genetic code should be robust to point nucleotide mutation and minimize the possibility of reversion from new to old information. In order to do so, we follow graph theory to study the properties of optimal codon sets, which can encode 20 canonical amino acids and stop coding signal. Finally, we describe the set of vacant codons that could be assigned to new amino acids. Moreover, we discuss the optimal number of the newly incorporated ncAAs and also the optimal size of codon blocks that are assigned to ncAAs.

synthetic biology↗

bioRxiv2019

Basic principles of the genetic code extension

Compounds including non-canonical amino acids or other artificially designed molecules can find a lot of applications in medicine, industry and biotechnology. They can be produced thanks to the modification or extension of the standard genetic code (SGC). Such peptides or proteins including the non-canonical amino acids can be constantly delivered in a stable way by organisms with the customized genetic code. Among several methods of engineering the code, using non-canonical base pairs is especially promising, because it enables generating many new codons, which can be used to encode any new amino acid. Since even one pair of new bases can extend the SGC up to 216 codons generated by six-letter nucleotide alphabet, the extension of the SGC can be achieved in many ways. Here, we proposed a stepwise procedure of the SGC extension with one pair of non-canonical bases to minimize the consequences of point mutations. We reported relationships between codons in the framework of graph theory. All 216 codons were represented as nodes of the graph, whereas its edges were induced by all possible single nucleotide mutations occurring between codons. Therefore, every set of canonical and newly added codons induces a specific subgraph. We characterized the properties of the induced subgraphs generated by selected sets of codons. Thanks to that, we were able to describe a procedure for incremental addition of the set of meaningful codons up to the full coding system consisting of three pairs of bases. The procedure of gradual extension of the SGC makes the whole system robust to changing genetic information due to mutations and is compatible with the views assuming that codons and amino acids were added successively to the primordial SGC, which evolved to minimize harmful consequences of mutations or mistranslations of encoded proteins.

bioinformatics↗

bioRxiv2018

The structure of the genetic code as an optimal graph clustering problem

The standard genetic code (SGC) is the set of rules by which genetic information is translated into proteins, from codons, i.e. triplets of nucleotides, to amino acids. The questions about the origin and the main factor responsible for the present structure of the code are still under a hot debate. Various methodologies have been used to study the features of the code and assess the level of its potential optimality. Here, we introduced a new general approach to evaluate the quality of the genetic code structure. This methodology comes from graph theory and allows us to describe new properties of the genetic code in terms of conductance. This parameter measures the robustness of codon groups against the potential changes in translation of the protein-coding sequences generated by single nucleotide substitutions. We described the genetic code as a partition of an undirected and unweighted graph, which makes the model general and universal. Using this approach, we showed that the structure of the genetic code is a solution to the graph clustering problem. We presented and discussed the structure of the codes that are optimal according to the conductance. Despite the fact that the standard genetic code is far from being optimal according to the conductance, its structure is characterised by many codon groups reaching the minimum conductance for their size. The SGC represents most likely a local minimum in terms of errors occurring in protein-coding sequences and their translation.

systems biology↗